Yunhao (Andy) Ge 葛云皓 3rd Year CS Ph.D. Student ilab @ USC Rm B06, Hedco Neurosciences Building University of Southern California 3641 Watt Way, Los Angeles, CA 90089-2520, USA Email: yunhaoge at usc dot edu

About Me

I am now a 3rd-year PhD student in iLab at University of Southern University (USC), working with Prof. Laurent Itti. I also work closely with Dr. Ziyan Wu (UII America). Before that, I got my M.Sc. degree at Robotics Institute at Shanghai Jiao Tong University, advised by Prof. Yanzheng Zhao and Prof. Weixin Yan. And I got my B.Eng. degree of Mechatronics at Shandong University. I have been lucky to work with Prof. Dinggang Shen and Dr. Shu Liao during my internship at United Imaging Intelligence, as well as Prof. Cewu Lu and Dr. Shuyun Chong when I was a Computer Vision Engineer at Flexiv Robotics.

• Causal Explainable AI ((1) Understanding reasoning logic and causality of Neural Networks (NN) (2) Use explanation as feedback to help improve the performance of the original NN.)
• Interpretable human-AI interaction (understanding AI models beyond accuracy, such as disentangled representation learning, human-NN knowledge exchange, steerability, generalization, fairness and bias)
• Humanoid Neural Network (simulating human cognitive learning ability (Imagination, Reasoning, Visual Recognition) by using various learning algorithms (Generative models, Representation Learning, Graph Neural Network, Contrastive Learning, etc.)
• Effortless AI (how generative models reduce human effort and boost discriminative models)

Research opportunities: I am happy to collaborate and/or answer questions about my research and USC academic programs. If you are interested, please send me an email. I especially encourage USC master students who want to involve exciting projects targeting top-tier conferences/journals to reach out.

News & Updates

[2021/08/23] I will be joining Google Cloud AI as a student researcher, advised by Dr. Sercan Arik and Dr. Jinsung Yoon

[2021/07/15] USC News , Tech Xplore , Technology Networks and other media pressed our ICLR 2021 paper: Group-Supervised Learning (Enabling the 'imagination' of artificial intelligence)

[2021/05/17] I will be joining Computer Vision Group at Microsoft Research Redmond as a research intern in summer 2021, advised by Dr. Vibhav Vineet and Dr. Neel Joshi

[2021/05/08] Serving as a reviewer for NeurIPS 2021 and ICLR 2022!

[2021/04/07] Releasing Img2SceneGraph, a pipeline that transfers images to scene graphs with node attributes! Welcome to Download and try!

[2021/04/02] One paper (Graph Autoencoder for Graph Compression and Representation Learning) was accepted by Neural Compression Workshop @ICLR 2021 as Spotlight!

[2021/02/28] One paper (A Peek Into the Reasoning of Neural Networks: Interpreting with Structural Visual Concepts) was accepted by CVPR 2021!

[2021/01/16] One paper (Beneficial Perturbation Network for designing general adaptive artificial intelligence systems) was accepted by TNNLS!

[2021/01/12] One paper (Zero-shot Synthesis with Group-Supervised Learning) was accepted by ICLR 2021!

[2020/09/14] Fonts dataset was proposed for fast testing and idea iteration on disentangled representation learning and zero-shot synthesis. Welcome to Download and try!

[2020/07/02] One paper (Pose Augmentation: Class-agnostic Object Pose Transformation) was accepted by ECCV 2020!

[2020/05/12] I will be joining UII America as a research intern in summer 2020, advised by Dr. Ziyan Wu and Dr. Srikrishna Karanam

[2019/08/12] I will be joining USC CS Ph.D. Program in fall 2019, advised by Prof. Laurent Itti.

[2019/07/01] One paper (Synthesis and inpainting-based MR-CT registration) was accepted by MICCAI 2019.

[2019/03/01] One paper (Unpaired Whole-Body Mr to CT Synthesis) was accepted by ISBI 2019.

Selected Publications [Google Scholar]

	A Peek Into the Reasoning of Neural Networks: Interpreting with Structural Visual Concepts TL;DR: Takes a step towards mimicking the reasoning process of NNs and provide logical, concept-level explanations for final model decisions. Yunhao Ge, Yao Xiao, Zhi Xu, Meng Zheng, Srikrishna Karanam, Terrence Chen, Laurent Itti and Ziyan Wu IEEE/ CVF International Conference on Computer Vision and Pattern Recognition (CVPR), 2021. [paper] [github] [website] [video] [知乎] [机器之心] [AI科技评论]
	Graph Autoencoder for Graph Compression and Representation Learning TL;DR: Multi-kernel Inductive Attention Graph Autoencoder (MIAGAE) utilizes the node similarity and graph structure to compress all nodes and edges as a whole. Yunhao Ge*, Yunkui Pang*, Linwei Li and Laurent Itti (*=equal contribution) Neural Compression: From Information Theory to Applications--Workshop@ (ICLR), 2021. [paper] [code] [Img2SceneGraph] Spotlight Presentation
	Zero-shot Synthesis with Group-Supervised Learning TL;DR: Using Controllable disentangled representation learning to simulate human knowledge factorization for imagination Yunhao Ge, Sami Abu-El-Haija, Gan Xin and Laurent Itti International Conference on Learning Representations (ICLR), 2021. [paper] [code] [website] [Fonts Dataset] [USC Viterbi Press] [知乎] [AI科技评论] [ USC News ] [ Tech Xplore ] [ Technology Networks ]
	Pose Augmentation: Class-agnostic Object Pose Transformation for Object Recognition TL;DR: Eliminate-add generator to explicitly disentangle pose from object identity by maximizing pose entropy Yunhao Ge, Jiaping Zhao, Laurent Itti European Conference on Computer Vision (ECCV), 2020. [paper] [github] [video-1min] [video-10min]
	Beneficial Perturbation Network for designing general adaptive artificial intelligence systems TL;DR:Allowing a single network to learn potentially unlimited parallel input to output mappings, and to switch on the fly between them at runtime. Shixian Wen, Amanda Rios*, Yunhao Ge* and Laurent Itti (*=equal contribution) IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021. [paper]
	Unpaired MR to CT Synthesis with Explicit Structural Constrained Adversarial Learning Yunhao Ge*, Dongming Wei*, Zhong Xue, Yiqiang Zhan, Xiang Zhou, Qian Wang and Shu Liao (*=equal contribution) IEEE International Symposium on Biomedical Imaging (ISBI), 2019. [paper] [code]
	Synthesis and inpainting-based MR-CT registration for image-guided thermal ablation of liver tumors Dongming Wei, Sahar Ahmad, Jiayu Huo, Wen Peng, Yunhao Ge, Zhong Xue, Pew-Thian Yap, Wentao Li, Dinggang Shen, Qian Wang International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2019. [paper]
	Unpaired Whole-body MR to CT Synthesis with Correlation Coefficient Constrained Adversarial Learning Yunhao Ge, Zhong Xue, Yiqiang Zhan, Xiang Zhou and Shu Liao SPIE-Medical Imaging (SPIE), 2019. [paper] [code] Oral Presentation
	Melanoma Segmentation and Classification in Clinical Images Using Deep Learning Yunhao Ge, Bin Li and Weixin Yan ACM International Conference on Machine Learning and Computing (ICMLC), 2018. [paper][Paper Link]

Intern & Work Experience

Google Cloud AI, Mountain View, USA (Aug. 2021 - current)

• Position: Student Researcher in Google Cloud AI
• Supervisor: Sercan Arik and Dr. Jinsung Yoon
• Project: Causal Explainable AI

Microsoft Research, Redmond, USA (May. 2021 - Aug. 2021)

• Position: Research Intern in Computer Vision Group
• Supervisor: Dr. Vibhav Vineet and Dr. Neel Joshi
• Project: Generative models boost discriminative and few shot learning

UII America, Inc, Boston, USA (May. 2020 - Aug. 2020)

• Position: Research Intern in UII America
• Supervisor: Dr. Ziyan Wu and Dr. Srikrishna Karanam
• Project: Explain reasoning logic of NN --> CVPR 2021

Flexiv Ltd, Shanghai, China (May. 2019 - Aug. 2019)

• Position: Computer Vision Engineer in Flexiv Robotics
• Supervisor: Prof. Cewu Lu and Dr. Shuyun Chong
• Project: Robotics adaptive massage based on human pose detection and tracking

United Imaging Intelligence Co., Ltd, Shanghai, China (Jun. 2018 - Apr. 2019)

• Position: Research Intern in United Imaging Intelligence
• Supervisor: Prof. Dinggang Shen and Dr. Shu Liao
• Project: Unpaired MR to CT image synthesis --> ISBI 2019 MICCAI 2019

Scholarships

• Aug 2019 Annenberg Graduate Fellowship at University of Southern California
• Sep 2017 National Scholarship(Graduate), (highest honor for graduates) top 1% nationwide
• Sep 2015 National Scholarship(Undergraduate), (highest honor for undergraduates, top 2% nationwide)
• May 2018 KaiYuan Motivational Scholarship top 0.5% in Shanghai Jiao Tong University
• Sep 2015 Presidential Scholarship, (highest honor in Shandong University) top 0.2% in Shan Dong University
• Sep 2015 BaoGang Excellent student Scholarship, (4 Places per year at Shandong University)
• Sep 2015 & Sep 2014 & Sep 2015 First Prize Scholarship (Top 6% in China,three-year continuous)

Honors and Awards

• Aug 2017 The First Prize 2017 ROBOMASTER The World’s Leading Robotics Competition (Responsible for the design of electronic control in robotics)[Code-T_Infantry]
• Aug 2017 Rank 1st (preliminary competition) , Tianchi: Precision medical competition-Artificial Intelligence Aided genetic risk prediction of diabetes [Code-Pred_diabetes]
• Oct 2015 The First Prize 9th international college students ican innovation and entrepreneurship contest
• Oct 2015 The Special prize(Top 1%) 6th National University Students Process Equipment Practice and Innovation Competition
• Aug 2015 The Silver prize 8th national college students in energy saving social practice and science and technology competition

Academic Service

Software & Patents

	Systems and methods for image processing S Liao, GE Yunhao, WEI Dongming US Patent App. 16/729,303.
	Pulmonary Nodular Assisted Detection System Based on AI(V1.0) Bin Li, Yunhao Ge 2018SR037095.
	A Two-Layer Barrier Free Parking Equipment Based on Bionic Manipulator Yunhao Ge, Shangze Yang, Zheng Zhang, Weixin Yan and Yanzheng Zhao CN201610712048.
	A Double Decker Parking Equipment based on Shear Lifting Mechanism and Hydraulic Mechanism Yunhao Ge, Xulong Zhou, Peng Liu and Yanzheng Zhao CN201610704408.

Last update: Oct. 2, 2021